{"id":"W4392760664","doi":"10.5194/egusphere-egu24-14889","title":"Compound events drowned in climate noise? The benefits of employing a regional SMILE in compound hot and dry summer assessment ","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dry climate; Noise (video); Environmental science; Climate change; Geology; Climatology; Computer science; Oceanography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002963382,0.0004204209,0.0004391667,0.0005804268,0.0003593375,0.001215594,0.0007037958,0.0005325617,0.001679484],"category_scores_gemma":[0.00814878,0.0001654001,0.0005985173,0.0007656333,0.000398512,0.001542533,0.001072941,0.0008373174,0.00028018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000483207,"about_ca_system_score_gemma":0.0008532371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03873056,"about_ca_topic_score_gemma":0.07126625,"domain_scores_codex":[0.9992701,0.0003031474,0.00004320722,0.0001626092,0.0001219995,0.00009889429],"domain_scores_gemma":[0.9978132,0.0007801711,0.0004012831,0.0004161831,0.000440664,0.0001483188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001255181,0.0001297239,0.4930639,0.0002583386,0.0007872427,0.0006403883,0.001344287,0.3114702,0.004520412,0.01958107,0.01652256,0.1504267],"study_design_scores_gemma":[0.00005085543,0.0002764886,0.486835,0.0001934385,0.0003836531,0.0001901112,0.002153529,0.4540383,0.004511117,0.01750519,0.03370348,0.0001587733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8978478,0.0008367395,0.07627316,0.002177633,0.0003441787,0.00009824028,0.005811468,0.0005470393,0.01606378],"genre_scores_gemma":[0.9892734,0.0001525789,0.007601655,0.0001530776,0.00008660927,0.00002934925,0.00204339,0.00007458529,0.0005853979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03873056,"threshold_uncertainty_score":0.07701027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05337177957306129,"score_gpt":0.33177981148212,"score_spread":0.2784080319090587,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}